UAEU research sheds new light on the pursuit of happiness at work

Thu, 18 May 2017

Groundbreaking big-data research produced by the United Arab Emirates University (UAEU)
suggests that, when it comes to keeping employees, it’s less important for them to
be happy – and more important for them to feel they are liked.

A study led by Dr. Jose Berengueres, Assistant Professor in UAEU’s Department of Computer
Science and the university’s Advanced Analytics Group has assessed “happiness data’
from 4,000 people working in 34 companies across Europe, in order to predict staff
turnover and identify precisely what causes the smile that makes them want to stay.

The results of the research collaboration between myhappyforce – an app-based platform
that measures, and aims to improve, happiness in the workplace – and the UAEU team
will be presented at the pydata.org conference at Barcelona-based management education school ESADE on 19th May, and
the prestigious 2017 IEEE/ACM International Conference on Advances in Social Networks
Analysis and Mining, Sydney, Australia, where the topic will be a key area of focus.

The study is one of the largest and most comprehensive data-collection projects on
global happiness ever conducted, and has produced the biggest dataset of its kind
on the subject to date which has been open sourced by UAEU. As governments, businesses,
and institutions look to leverage workplace happiness with a view to increasing productivity
and reducing employee churn, it has produced some eye-catching and thought-provoking
findings.

Through developing a model capable of predicting whether a worker is likely to quit
their job in the next three months with 75% accuracy, the research team found that
the most reliable predictor was not whether an employee says they are happy, but “likeability”
– the ratio of likes versus dislikes received by their comments on workplace social
forums, dictated by factors they cannot control. Meanwhile, the findings also suggest
that the notion of ‘Monday morning blues’, as the Western working week begins, may
need to be revisited – as other days of the week actually bring a greater amount of
gloom.

“Happiness is considered to be good for business and good for governments,” said Dr.
Berengueres. “On the other hand, a significant body of research shows that being happy
all the time is not necessarily natural or healthy, and can be exhausting. To further
complicate matters, happiness is subjective, hard to define, and difficult to measure.

“Of all the factors that influence happiness, work - or the lack of it - is the single
most important predictor of happiness. The World Happiness Report states that being
unemployed causes people to be miserable. But, through this study, we aimed to look
at this topic in the context of those who have jobs.”

The team – comprising project lead Dr. Berengueres, UAEU research assistant Guilem
Duran, and myhappyforce’s chief technical officer Daniel Castro – modeled happiness
data collated by myhappyforce from thousands of workers over a two-and-a-half-year
period and used it to predict turnover, before conducting deeper investigations, using
more than 100 different measurements, into the characteristics of this data which
are most closely linked to an employee leaving their job.

The app allowed employees not only to log how happy they felt in their work, but also
to send a suggestion or comment to a company forum once a day – in the form of “water-cooler
chat”, according to Dr. Berengueres – and view and ‘like’ the reaction from peers.
“Messages on this forum were a channel for employees to send feedback to management
without fear of repercussions, and a way for management to know what their workforce
is actually thinking,” said Dr. Berengueres.

The strength of the results allowed the team to group employees into two distinct
clusters: “A-type employees”, who account for 75% of the workforce studied and have
a high “likeability ratio”; and “B-type employees”, who did not provide feedback and
therefore did not see their comments receive many ‘likes’. The study found that B-type
employees were three times more likely to quit in the following quarter of the year
than their A-type counterparts.

“Another surprising finding was that the indicators that better predict employee churn
are not related to individuals, but are those that relate an employee to their peers’
metrics. We were also able to measure how a particular day of the week affects employees’
self-perceived happiness – contrary to popular belief, Tuesday and Wednesday, rather
than Monday, are the least happy days, by a thin margin, and Saturday is the happiest
day.”

According to Dr. Berengueres, a company’s employee-churn is connected to, and governed
by, “a series of features”, some of which are the sole preserve of the individual
employee, such as their personal happiness. However, he said: “None of the top features
identified through this study are completely internal to the employee, on the contrary
they depend on extrinsic factors that are outside the employee’s control, such as
the number of likes they receive and the relative happiness of their peers."

“If we hypothesize that a happy workforce is correlated with less churn, so are the
features that generate happiness. This leads to the conclusion that, when it comes
to work, happiness is not as much of an ‘inside job”, as is sometimes claimed, but
is actually significantly dependent on factors outside the control of the employee.”

Daniel Castro further added that: “This study not only confirms that people need to
share and validate opinions or thoughts with their peers, but also shows how important
it is for organizations to invest resources in listening to and understanding how
employees relate in the workplace”.